io.github.borgi-s/dfxm-geo-mcp

Official

by borgi-s · Python

MCP server for the dfxm-geo dark-field X-ray microscopy forward model

Forward model server for dark-field X-ray microscopy computational analysis.

dfxm-geo-mcp

An MCP server that lets an AI client drive the dfxm-geo dark-field X-ray microscopy forward model: validate and scaffold configs, enumerate reachable reflections, and render preview-scale simulations.

Claude Desktop rendering a DFXM image from a plain-English request

Run

code

uvx dfxm-geo-mcp

Claude Desktop (claude_desktop_config.json):

code

{"mcpServers": {"dfxm-geo": {"command": "uvx", "args": ["dfxm-geo-mcp"]}}}

Or: pip install dfxm-geo-mcp then dfxm-geo-mcp.

First run pulls a heavy scientific stack (numba/scipy) and warms a JIT cache (~10 s once). No fake demo mode — the sims are real.

Tools

validate_config · find_reflections · predict_visibility (g·b reflection-visibility ranking; structured scores plus a self-contained .html) · scaffold_config · run_forward (analytic preview; saves a PNG and a self-contained .html) · run_rocking (interactive φ-rocking-curve viewer: a single self-contained .html with a frame scrubber + live rocking-curve plot) · start_bootstrap / get_job_status / get_job_result (MC fidelity).

Both run_forward and run_rocking write self-contained HTML (image(s) embedded, all CSS/JS inline, no external origins) that opens full-size in any browser and is surfaced by file-showing clients.

Architecture

A protocol-agnostic ops layer wrapping dfxm-geo, under a thin FastMCP adapter. See docs/superpowers/specs/.

Roadmap (v2)

run_identify · remote HTTP transport · .mcpb bundle.

Install

claude_desktop_config.json

{
  "mcpServers": {
    "dfxm-geo-mcp": {
      "command": "uvx",
      "args": [
        "dfxm-geo-mcp"
      ]
    }
  }
}